F-DCS: FMI-Based Distributed CPS Simulation Framework with a Redundancy Reduction Algorithm.

Area of Science:

• Cyber-Physical Systems (CPS)
• Electric Vehicle (EV) Simulation
• Distributed Control Systems

Background:

• Electric vehicles (EVs) are complex cyber-physical systems (CPS) requiring quantitative analysis and simulation for performance prediction.
• Existing simulation methods for EVs can be time-consuming due to the intricate nature of their interconnected cyber and physical components.

Purpose of the Study:

• To propose and validate an FMI-based distributed CPS simulation framework (F-DCS) for electric vehicle (EV) simulations.
• To enhance simulation efficiency and accuracy using a novel redundancy reduction algorithm (RRA).

Main Methods:

• Development of an FMI-based distributed CPS simulation framework (F-DCS).
• Integration of a redundancy reduction algorithm (RRA) to predict and minimize repetitive patterns during simulation.
• Validation through simulating an electric vehicle (EV) model using the proposed F-DCS with RRA.

Main Results:

• The F-DCS with RRA demonstrated a significant reduction in simulation time (over 30%) compared to conventional methods.
• The proposed framework maintained conventional accuracy in EV performance prediction.
• The F-DCS incorporating RRA provided results reflecting real-time sensor information.

Conclusions:

• The proposed FMI-based distributed CPS simulation framework (F-DCS) with a redundancy reduction algorithm (RRA) offers an efficient solution for EV validation.
• This approach accelerates EV simulation while preserving accuracy, enabling better performance prediction for complex cyber-physical systems.